This project is using Python to build a spam filter with Naive Bayes, Support Vector Machine (SVM) and Neural Network using Enron Email Corpus(ham:16454, spam:17171). (http://www.cs.cmu.edu/~enron/). Useful information can be found at http://www.aueb.gr/users/ion/docs/ceas2006_paper.pdf.

scikit-learn http://scikit-learn.org/stable/

NLTK http://nltk.org/

BeautifulSoup http://www.crummy.com/software/BeautifulSoup/

Scipy http://www.scipy.org/

Numpy http://www.numpy.org/

1. Loading enron emails corpus into memory

2. Tokenizing files into word, and store them into lists

3. Feature extraction

4. Feature selection based on the words from corpus

5. Training classifiers with Naive Bayes, SVM and AdaBoosting algorithms

6. Evaluating the classifier

7. Using Adaboost method to improve the accuaracy

8. Checking results and improve the speed using Numpy & Scipy

1). more datasets 2). reduce demonsionality 3). add prori probability 4). optimizate the program

1. Web Data Mining

2. Programming Collective Intelligence

3. Machine Learning in Action

4. Scipy and Numpy

5. Building Machine System with Python